In the paper authors consider the active suspension of the wheeled vehicle. The proposed controller consists of a sliding mode controller used to roll reduction and linear regulators with quadratic performance index (LQRs) for struts control was shown. The energy consumption optimization was taken into account at the stage of strut controllers synthesis. The studied system is half of the active vehicle suspension using hydraulic actuators to increase the ride comfort and keeping safety. Instead of installing additional actuators in the form of active anti-roll bars, it has been decided to expand the active suspension control algorithm by adding extra functionality that accounts for the roll. The suggested algorithm synthesis method is based on the object decomposition into two subsystems whose controllers can be synthesized separately. Individual suspension struts are controlled by actuators that use the controllers whose parameters have been calculated with the LQR method. The mathematical model of the actuator applied in the work takes into account its nonlinear nature and the dynamics of the servovalve. The simulation tests of the built active suspension control system have been performed. In the proposed solution, the vertical displacements caused by uneven road surface are reduced by controllers related directly to suspension strut actuators.

This paper presents a learning system with a K-nearest neighbour classifier to classify the wear condition of a multi-piston positive displacement pump. The first part reviews current built diagnostic methods and describes typical failures of multi-piston positive displacement pumps and their causes. Next is a description of a diagnostic experiment conducted to acquire a matrix of vibration signals from selected locations in the pump body. The measured signals were subjected to time-frequency analysis. The signal features calculated in the time and frequency domain were grouped in a table according to the wear condition of the pump. The next step was to create classification models of a pump wear condition and assess their accuracy. The selected model, which best met the set criteria for accuracy assessment, was verified with new measurement data. The article ends with a summary.

Studies of systems with energy regeneration have been carried out for years, because they primarily cover the assemblies with electrodynamic actuators. This paper addresses the issue of active reduction of mechanical vibration using an electrohydraulic actuator. The testing procedure aims to assess the potential use of those assemblies in a different frequency band and force range than in electrodynamic actuators. The paper explains the operating principle of the system, and the findings of laboratory tests are presented. The tested vibration reducing system is the physical model of a 2 degree-of-freedom (DOF) suspension. An initial analysis has been conducted to explore the potential use of the energy produced by the vibration of unsprung mass in the first degree of the suspension system, for power supply to the active component incorporated in the second suspension degree. The energy recuperated from the first suspension DOF is transferred by a dedicated hydraulic system and stored in an accumulator. Results of the experiments revealed that the mechanical parameters of the system can be selected in such a way that for specific interfering signals the accumulated energy should be at least equal to the energy used up by the system.

This paper is focused on the problem of active suspensions of wheeled vehicles with electro-hydraulic actuators. Two dynamic structures first with actuator connected with spring in series and second in parallel – called slow active and full active respectively – were considered. The considerations described in the paper concern physical quarter-vehicle models of suspensions. These models were constructed and installed on a rig for dynamic tests of structures. A laboratory rig enables the simulation of real conditions by disturbing investigated suspension by kinematic excitation. Research was carried out for various algorithms controlling the actuator of the active unit. For evaluation of laboratory research results, comparisons were proposed of frequency response functions and of time curves of instantaneous power taken by the active system from supply, obtained at the same excitation signals. Quantitative aggregated indicators in the form of an averaged coefficient of vibration transmissibility and power required for the active unit to achieve vibration transmissibility function were also proposed.

Laboratory investigations of an active vehicle suspension of an in-series structure of the slow-active type are presented in this paper. The multidimensional model is reduced to a case representing quarter car suspension. Control laws for active vibration reduction systems are usually determined based upon linear models of objects. Active suspensions are characterised by nonlinearity, connected most often with actuating systems and their energetic restrictions. This causes divergences between theoretical quality factors and those determined experimentally. The second essential problem is finding a compromise between opposed quality factors (for example, minimum power requirement and high efficiency of vibration reduction). Thanks to the use of the proper control law in the active vibration reduction system of vehicle suspension, the goal of ensuring a high level of ride comfort, good vehicle handling and incessant contact of the wheels with the road surface with a minimum power requirement may be attained. The authors, in seeking a compromise, determined classical LQR controllers for the proposed quality indicators realising the aims mentioned above. These controllers are determined for a linearised suspension model obtained from identification. Experimental characteristics are determined for all of the suspension control systems.

This paper presents the use of one-way analysis of variance ANOVA as an effective tool for ranking the features calculated from diagnostic signals and evaluates their impact on the accuracy of the machine learning system's classification of displacement pump wear.The first part includes a review of contemporary diagnostic systems and a description of typical damage of multi-piston displacement pumps and Its causes. The work also contains description of a diagnostic experiment which was conducted in order to obtain the matrix of vibration signals and the matrix of pressures measured at selected locations on the pump housing and at the pump pressure line. The measured signals were subjected to time–frequency analysis. The features of signals calculated in the time and frequency domains were ranked using the ANOVA. The next step involved the use the available classifiers in pump wear evaluation, conducting tests and assessing their effectiveness in terms of the ranking of features and the origin of diagnostic signals.